{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MovieLens的数据集——数据探索\n",
    "\n",
    "数据集包含三个主要文件：\n",
    "1. 用户电影打分三元表：u.data\n",
    "4个字段：\n",
    "1）user_id：用户ID\n",
    "2）movie_id：电影ID\n",
    "3）rating：用户打分\n",
    "4）timestamp：表示用户打分的时间，unix seconds since 1/1/1970 UTC\n",
    "\n",
    "2. 用户基本信息表：u.user\n",
    "共5个字段：\n",
    "1）user_id：用户ID\n",
    "2）age：年龄\n",
    "3）gender：性别\n",
    "4）occupation：职业\n",
    "5）zip_code：邮编\n",
    "\n",
    "3. 电影基本信息表：u.item\n",
    "共5 + 19 个字段：\n",
    "1）movie_id：电影ID\n",
    "2）title：电影标题（带年份）\n",
    "3）release_date：电影发布日期\n",
    "4）video_release_date：Video发布日期\n",
    "5）imdb_url：链接\n",
    "\n",
    "6-25）genres（共19维）：\n",
    "'unknown', 'Action', 'Adventure',\n",
    "'Animation', 'Children\\'s', 'Comedy', 'Crime', 'Documentary', 'Drama', 'Fantasy',\n",
    "'Film-Noir', 'Horror', 'Musical', 'Mystery', 'Romance', 'Sci-Fi', 'Thriller', 'War', 'Western'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## import工具包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import datetime\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 读入评分数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>item_id</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>196</td>\n",
       "      <td>242</td>\n",
       "      <td>3</td>\n",
       "      <td>881250949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>186</td>\n",
       "      <td>302</td>\n",
       "      <td>3</td>\n",
       "      <td>891717742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>22</td>\n",
       "      <td>377</td>\n",
       "      <td>1</td>\n",
       "      <td>878887116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>244</td>\n",
       "      <td>51</td>\n",
       "      <td>2</td>\n",
       "      <td>880606923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>166</td>\n",
       "      <td>346</td>\n",
       "      <td>1</td>\n",
       "      <td>886397596</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id  item_id  rating  timestamp\n",
       "0      196      242       3  881250949\n",
       "1      186      302       3  891717742\n",
       "2       22      377       1  878887116\n",
       "3      244       51       2  880606923\n",
       "4      166      346       1  886397596"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#读取数据\n",
    "triplet_cols = ['user_id','item_id', 'rating', 'timestamp'] \n",
    "\n",
    "dpath = './data/'\n",
    "df_triplet = pd.read_csv(dpath +'u.data', sep='\\t', names=triplet_cols, encoding='latin-1')\n",
    "df_triplet.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 100000 entries, 0 to 99999\n",
      "Data columns (total 4 columns):\n",
      "user_id      100000 non-null int64\n",
      "item_id      100000 non-null int64\n",
      "rating       100000 non-null int64\n",
      "timestamp    100000 non-null int64\n",
      "dtypes: int64(4)\n",
      "memory usage: 3.1 MB\n"
     ]
    }
   ],
   "source": [
    "df_triplet.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100000, 4)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_triplet.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>item_id</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>196</td>\n",
       "      <td>242</td>\n",
       "      <td>3</td>\n",
       "      <td>1997-12-04 23:55:49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>186</td>\n",
       "      <td>302</td>\n",
       "      <td>3</td>\n",
       "      <td>1998-04-05 03:22:22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>22</td>\n",
       "      <td>377</td>\n",
       "      <td>1</td>\n",
       "      <td>1997-11-07 15:18:36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>244</td>\n",
       "      <td>51</td>\n",
       "      <td>2</td>\n",
       "      <td>1997-11-27 13:02:03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>166</td>\n",
       "      <td>346</td>\n",
       "      <td>1</td>\n",
       "      <td>1998-02-02 13:33:16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id  item_id  rating           timestamp\n",
       "0      196      242       3 1997-12-04 23:55:49\n",
       "1      186      302       3 1998-04-05 03:22:22\n",
       "2       22      377       1 1997-11-07 15:18:36\n",
       "3      244       51       2 1997-11-27 13:02:03\n",
       "4      166      346       1 1998-02-02 13:33:16"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_triplet['timestamp'].astype('float64')\n",
    "df_triplet['timestamp']=df_triplet['timestamp'].map(datetime.datetime.fromtimestamp) # 时间格式转换\n",
    "df_triplet.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算用户数、电影数目"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of users = 943\n",
      "Number of movies = 1682\n"
     ]
    }
   ],
   "source": [
    "n_users = df_triplet['user_id'].unique().shape[0]\n",
    "n_items = df_triplet['item_id'].unique().shape[0]\n",
    "print ('Number of users = ' + str(n_users) + '\\n'+ 'Number of movies = ' + str(n_items) )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算每个用户的评分次数\n",
    "看哪些用户最活跃"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.series.Series'>\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "147    20\n",
       "19     20\n",
       "572    20\n",
       "636    20\n",
       "895    20\n",
       "Name: user_id, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 统计每部电影的评分人数，可看出电影的流行程度，默认是降序排列\n",
    "user_freq = df_triplet['user_id'].value_counts() \n",
    "print(type(df_triplet['user_id']))\n",
    "user_freq.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Int64Index([405, 655,  13, 450, 276, 416, 537, 303, 234, 393,\n",
      "            ...\n",
      "             93, 732, 475, 571, 596, 147,  19, 572, 636, 895],\n",
      "           dtype='int64', length=943)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(user_freq.index, user_freq)\n",
    "print(user_freq.index)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算每个电影的评分次数\n",
    "看哪些电影最流行(被评分次数最多)\n",
    "基于流行度的推荐可以推荐最流行的电影"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_id</th>\n",
       "      <th>rating_times</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>50</td>\n",
       "      <td>583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>258</td>\n",
       "      <td>509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>100</td>\n",
       "      <td>508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>181</td>\n",
       "      <td>507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>294</th>\n",
       "      <td>294</td>\n",
       "      <td>485</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     item_id  rating_times\n",
       "50        50           583\n",
       "258      258           509\n",
       "100      100           508\n",
       "181      181           507\n",
       "294      294           485"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 统计每部电影的评分人数，可看出电影的流行程度，默认是降序排列\n",
    "items_rating_times = df_triplet['item_id'].value_counts() \n",
    "#item_freq.head()\n",
    "# print(items_rating_times)\n",
    "df_items_sorted_by_rating_times = pd.DataFrame({'item_id':items_rating_times.index, 'rating_times':items_rating_times})\n",
    "# items_rating_times.head()\n",
    "df_items_sorted_by_rating_times.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#按索引排列\n",
    "plt.bar(items_rating_times.index, items_rating_times)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Int64Index([  50,  258,  100,  181,  294,  286,  288,    1,  300,  121,\n",
      "            ...\n",
      "            1670, 1606, 1520, 1414, 1584, 1648, 1571, 1329, 1457, 1663],\n",
      "           dtype='int64', length=1682)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#按评分次数排列\n",
    "# print(items_rating_times.index)\n",
    "items_rating_times1 = items_rating_times.copy()\n",
    "items_rating_times1.index = range(items_rating_times1.count()) # 对索引重新赋值，方便画图\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "items_rating_times1.plot(ax=ax, title='Rating Times');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 看看最流行的是哪些电影，与u.item关联"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_id</th>\n",
       "      <th>title</th>\n",
       "      <th>release_date</th>\n",
       "      <th>video_release_date</th>\n",
       "      <th>imdb_url</th>\n",
       "      <th>unknown</th>\n",
       "      <th>Action</th>\n",
       "      <th>Adventure</th>\n",
       "      <th>Animation</th>\n",
       "      <th>Children's</th>\n",
       "      <th>...</th>\n",
       "      <th>Fantasy</th>\n",
       "      <th>Film-Noir</th>\n",
       "      <th>Horror</th>\n",
       "      <th>Musical</th>\n",
       "      <th>Mystery</th>\n",
       "      <th>Romance</th>\n",
       "      <th>Sci-Fi</th>\n",
       "      <th>Thriller</th>\n",
       "      <th>War</th>\n",
       "      <th>Western</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>01-Jan-1995</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Toy%20Story%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>GoldenEye (1995)</td>\n",
       "      <td>01-Jan-1995</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?GoldenEye%20(...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Four Rooms (1995)</td>\n",
       "      <td>01-Jan-1995</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Four%20Rooms%...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Get Shorty (1995)</td>\n",
       "      <td>01-Jan-1995</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Get%20Shorty%...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Copycat (1995)</td>\n",
       "      <td>01-Jan-1995</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Copycat%20(1995)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   item_id              title release_date  video_release_date  \\\n",
       "0        1   Toy Story (1995)  01-Jan-1995                 NaN   \n",
       "1        2   GoldenEye (1995)  01-Jan-1995                 NaN   \n",
       "2        3  Four Rooms (1995)  01-Jan-1995                 NaN   \n",
       "3        4  Get Shorty (1995)  01-Jan-1995                 NaN   \n",
       "4        5     Copycat (1995)  01-Jan-1995                 NaN   \n",
       "\n",
       "                                            imdb_url  unknown  Action  \\\n",
       "0  http://us.imdb.com/M/title-exact?Toy%20Story%2...        0       0   \n",
       "1  http://us.imdb.com/M/title-exact?GoldenEye%20(...        0       1   \n",
       "2  http://us.imdb.com/M/title-exact?Four%20Rooms%...        0       0   \n",
       "3  http://us.imdb.com/M/title-exact?Get%20Shorty%...        0       1   \n",
       "4  http://us.imdb.com/M/title-exact?Copycat%20(1995)        0       0   \n",
       "\n",
       "   Adventure  Animation  Children's  ...  Fantasy  Film-Noir  Horror  Musical  \\\n",
       "0          0          1           1  ...        0          0       0        0   \n",
       "1          1          0           0  ...        0          0       0        0   \n",
       "2          0          0           0  ...        0          0       0        0   \n",
       "3          0          0           0  ...        0          0       0        0   \n",
       "4          0          0           0  ...        0          0       0        0   \n",
       "\n",
       "   Mystery  Romance  Sci-Fi  Thriller  War  Western  \n",
       "0        0        0       0         0    0        0  \n",
       "1        0        0       0         1    0        0  \n",
       "2        0        0       0         1    0        0  \n",
       "3        0        0       0         0    0        0  \n",
       "4        0        0       0         1    0        0  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#读取数据\n",
    "item_cols = ['item_id', 'title', 'release_date', 'video_release_date', 'imdb_url', 'unknown', 'Action', 'Adventure',\n",
    " 'Animation', 'Children\\'s', 'Comedy', 'Crime', 'Documentary', 'Drama', 'Fantasy',\n",
    " 'Film-Noir', 'Horror', 'Musical', 'Mystery', 'Romance', 'Sci-Fi', 'Thriller', 'War', 'Western'] \n",
    "\n",
    "dpath = './data/'\n",
    "df_items = pd.read_csv(dpath +'u.item', sep='|', names=item_cols,encoding='latin-1') \n",
    "df_items.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_id</th>\n",
       "      <th>rating_times</th>\n",
       "      <th>title</th>\n",
       "      <th>release_date</th>\n",
       "      <th>video_release_date</th>\n",
       "      <th>imdb_url</th>\n",
       "      <th>unknown</th>\n",
       "      <th>Action</th>\n",
       "      <th>Adventure</th>\n",
       "      <th>Animation</th>\n",
       "      <th>...</th>\n",
       "      <th>Film-Noir</th>\n",
       "      <th>Horror</th>\n",
       "      <th>Musical</th>\n",
       "      <th>Mystery</th>\n",
       "      <th>Romance</th>\n",
       "      <th>Sci-Fi</th>\n",
       "      <th>Thriller</th>\n",
       "      <th>War</th>\n",
       "      <th>Western</th>\n",
       "      <th>ranking_rating_times</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>50</td>\n",
       "      <td>583</td>\n",
       "      <td>Star Wars (1977)</td>\n",
       "      <td>01-Jan-1977</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Star%20Wars%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>258</td>\n",
       "      <td>509</td>\n",
       "      <td>Contact (1997)</td>\n",
       "      <td>11-Jul-1997</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/Title?Contact+(1997/I)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>100</td>\n",
       "      <td>508</td>\n",
       "      <td>Fargo (1996)</td>\n",
       "      <td>14-Feb-1997</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Fargo%20(1996)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>181</td>\n",
       "      <td>507</td>\n",
       "      <td>Return of the Jedi (1983)</td>\n",
       "      <td>14-Mar-1997</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Return%20of%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>294</td>\n",
       "      <td>485</td>\n",
       "      <td>Liar Liar (1997)</td>\n",
       "      <td>21-Mar-1997</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/Title?Liar+Liar+(1997)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   item_id  rating_times                      title release_date  \\\n",
       "0       50           583           Star Wars (1977)  01-Jan-1977   \n",
       "1      258           509             Contact (1997)  11-Jul-1997   \n",
       "2      100           508               Fargo (1996)  14-Feb-1997   \n",
       "3      181           507  Return of the Jedi (1983)  14-Mar-1997   \n",
       "4      294           485           Liar Liar (1997)  21-Mar-1997   \n",
       "\n",
       "   video_release_date                                           imdb_url  \\\n",
       "0                 NaN  http://us.imdb.com/M/title-exact?Star%20Wars%2...   \n",
       "1                 NaN          http://us.imdb.com/Title?Contact+(1997/I)   \n",
       "2                 NaN    http://us.imdb.com/M/title-exact?Fargo%20(1996)   \n",
       "3                 NaN  http://us.imdb.com/M/title-exact?Return%20of%2...   \n",
       "4                 NaN          http://us.imdb.com/Title?Liar+Liar+(1997)   \n",
       "\n",
       "   unknown  Action  Adventure  Animation  ...  Film-Noir  Horror  Musical  \\\n",
       "0        0       1          1          0  ...          0       0        0   \n",
       "1        0       0          0          0  ...          0       0        0   \n",
       "2        0       0          0          0  ...          0       0        0   \n",
       "3        0       1          1          0  ...          0       0        0   \n",
       "4        0       0          0          0  ...          0       0        0   \n",
       "\n",
       "   Mystery  Romance  Sci-Fi  Thriller  War  Western  ranking_rating_times  \n",
       "0        0        1       1         0    1        0                     0  \n",
       "1        0        0       1         0    0        0                     1  \n",
       "2        0        0       0         1    0        0                     2  \n",
       "3        0        1       1         0    1        0                     3  \n",
       "4        0        0       0         0    0        0                     4  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 根据频次大小依次取电影信息\n",
    "df_items_sorted_by_rating_times_merge = pd.merge(df_items_sorted_by_rating_times, df_items, how='left', left_on='item_id', right_on='item_id')\n",
    "df_items_sorted_by_rating_times_merge['ranking_rating_times']=range(items_rating_times.count()) # 加上排名,数字越小，排在越前面\n",
    "\n",
    "df_items_sorted_by_rating_times_merge.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'list'>\n",
      "[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19]\n",
      "[583, 509, 508, 507, 485, 481, 478, 452, 431, 429, 420, 413, 394, 392, 390, 384, 378, 367, 365, 350]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 前二十大流行电影\n",
    "popular_items_count_top_20 = df_items_sorted_by_rating_times_merge.iloc[0:20]['rating_times']\n",
    "popular_items_top_20_titles =  df_items_sorted_by_rating_times_merge.iloc[0:20]['title']\n",
    "\n",
    "objects = (list(popular_items_top_20_titles))\n",
    "print(type(objects))\n",
    "y_pos = np.arange(len(objects))\n",
    "print(y_pos)\n",
    "performance = list(popular_items_count_top_20)\n",
    "print(performance)\n",
    "plt.rcdefaults()    \n",
    "plt.bar(y_pos, performance, align='center', alpha=0.5)\n",
    "# 设置 x 坐标轴刻度\n",
    "plt.xticks(y_pos, objects, rotation='vertical')\n",
    "plt.ylabel('Rating Count')\n",
    "plt.title('Most popular Movies')\n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算每个电影的受欢迎程度\n",
    "看哪些电影的平均评分分数最高（总评分？）\n",
    "基于受欢迎的程度可以推荐最受欢迎的电影"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_id_col</th>\n",
       "      <th>mean_rating</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>item_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1293</th>\n",
       "      <td>1293</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1467</th>\n",
       "      <td>1467</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1653</th>\n",
       "      <td>1653</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>814</th>\n",
       "      <td>814</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1122</th>\n",
       "      <td>1122</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         item_id_col  mean_rating\n",
       "item_id                          \n",
       "1293            1293          5.0\n",
       "1467            1467          5.0\n",
       "1653            1653          5.0\n",
       "814              814          5.0\n",
       "1122            1122          5.0"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "items_mean_rating = df_triplet['rating'].groupby(df_triplet['item_id']).mean()\n",
    "items_mean_rating = items_mean_rating.sort_values(ascending = False)\n",
    "\n",
    "df_items_sorted_by_mean_rating = pd.DataFrame({'item_id_col':items_mean_rating.index, 'mean_rating':items_mean_rating})\n",
    "df_items_sorted_by_mean_rating.head()\n",
    "# df_items_sorted_by_mean_rating.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_id</th>\n",
       "      <th>rating_times</th>\n",
       "      <th>title</th>\n",
       "      <th>release_date</th>\n",
       "      <th>video_release_date</th>\n",
       "      <th>imdb_url</th>\n",
       "      <th>unknown</th>\n",
       "      <th>Action</th>\n",
       "      <th>Adventure</th>\n",
       "      <th>Animation</th>\n",
       "      <th>...</th>\n",
       "      <th>Film-Noir</th>\n",
       "      <th>Horror</th>\n",
       "      <th>Musical</th>\n",
       "      <th>Mystery</th>\n",
       "      <th>Romance</th>\n",
       "      <th>Sci-Fi</th>\n",
       "      <th>Thriller</th>\n",
       "      <th>War</th>\n",
       "      <th>Western</th>\n",
       "      <th>ranking_rating_times</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>50</td>\n",
       "      <td>583</td>\n",
       "      <td>Star Wars (1977)</td>\n",
       "      <td>01-Jan-1977</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Star%20Wars%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>258</td>\n",
       "      <td>509</td>\n",
       "      <td>Contact (1997)</td>\n",
       "      <td>11-Jul-1997</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/Title?Contact+(1997/I)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>100</td>\n",
       "      <td>508</td>\n",
       "      <td>Fargo (1996)</td>\n",
       "      <td>14-Feb-1997</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Fargo%20(1996)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>181</td>\n",
       "      <td>507</td>\n",
       "      <td>Return of the Jedi (1983)</td>\n",
       "      <td>14-Mar-1997</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Return%20of%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>294</td>\n",
       "      <td>485</td>\n",
       "      <td>Liar Liar (1997)</td>\n",
       "      <td>21-Mar-1997</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/Title?Liar+Liar+(1997)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   item_id  rating_times                      title release_date  \\\n",
       "0       50           583           Star Wars (1977)  01-Jan-1977   \n",
       "1      258           509             Contact (1997)  11-Jul-1997   \n",
       "2      100           508               Fargo (1996)  14-Feb-1997   \n",
       "3      181           507  Return of the Jedi (1983)  14-Mar-1997   \n",
       "4      294           485           Liar Liar (1997)  21-Mar-1997   \n",
       "\n",
       "   video_release_date                                           imdb_url  \\\n",
       "0                 NaN  http://us.imdb.com/M/title-exact?Star%20Wars%2...   \n",
       "1                 NaN          http://us.imdb.com/Title?Contact+(1997/I)   \n",
       "2                 NaN    http://us.imdb.com/M/title-exact?Fargo%20(1996)   \n",
       "3                 NaN  http://us.imdb.com/M/title-exact?Return%20of%2...   \n",
       "4                 NaN          http://us.imdb.com/Title?Liar+Liar+(1997)   \n",
       "\n",
       "   unknown  Action  Adventure  Animation  ...  Film-Noir  Horror  Musical  \\\n",
       "0        0       1          1          0  ...          0       0        0   \n",
       "1        0       0          0          0  ...          0       0        0   \n",
       "2        0       0          0          0  ...          0       0        0   \n",
       "3        0       1          1          0  ...          0       0        0   \n",
       "4        0       0          0          0  ...          0       0        0   \n",
       "\n",
       "   Mystery  Romance  Sci-Fi  Thriller  War  Western  ranking_rating_times  \n",
       "0        0        1       1         0    1        0                     0  \n",
       "1        0        0       1         0    0        0                     1  \n",
       "2        0        0       0         1    0        0                     2  \n",
       "3        0        1       1         0    1        0                     3  \n",
       "4        0        0       0         0    0        0                     4  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_items_sorted_by_rating_times_merge.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th>item_id</th>\n",
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       "      <th>0</th>\n",
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       "      <td>3</td>\n",
       "      <td>Star Kid (1997)</td>\n",
       "      <td>16-Jan-1998</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?imdb-title-12...</td>\n",
       "      <td>0</td>\n",
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       "      <td>1450</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1467</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1467</td>\n",
       "      <td>2</td>\n",
       "      <td>Saint of Fort Washington, The (1993)</td>\n",
       "      <td>01-Jan-1993</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Saint%20of%20...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>1483</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1653</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1653</td>\n",
       "      <td>1</td>\n",
       "      <td>Entertaining Angels: The Dorothy Day Story (1996)</td>\n",
       "      <td>27-Sep-1996</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Entertaining%...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1652</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>814</td>\n",
       "      <td>5.0</td>\n",
       "      <td>814</td>\n",
       "      <td>1</td>\n",
       "      <td>Great Day in Harlem, A (1994)</td>\n",
       "      <td>01-Jan-1994</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Great%20Day%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1661</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1122</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1122</td>\n",
       "      <td>1</td>\n",
       "      <td>They Made Me a Criminal (1939)</td>\n",
       "      <td>01-Jan-1939</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?They%20Made%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1615</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   item_id_col  mean_rating  item_id  rating_times  \\\n",
       "0         1293          5.0     1293             3   \n",
       "1         1467          5.0     1467             2   \n",
       "2         1653          5.0     1653             1   \n",
       "3          814          5.0      814             1   \n",
       "4         1122          5.0     1122             1   \n",
       "\n",
       "                                               title release_date  \\\n",
       "0                                    Star Kid (1997)  16-Jan-1998   \n",
       "1               Saint of Fort Washington, The (1993)  01-Jan-1993   \n",
       "2  Entertaining Angels: The Dorothy Day Story (1996)  27-Sep-1996   \n",
       "3                      Great Day in Harlem, A (1994)  01-Jan-1994   \n",
       "4                     They Made Me a Criminal (1939)  01-Jan-1939   \n",
       "\n",
       "   video_release_date                                           imdb_url  \\\n",
       "0                 NaN  http://us.imdb.com/M/title-exact?imdb-title-12...   \n",
       "1                 NaN  http://us.imdb.com/M/title-exact?Saint%20of%20...   \n",
       "2                 NaN  http://us.imdb.com/M/title-exact?Entertaining%...   \n",
       "3                 NaN  http://us.imdb.com/M/title-exact?Great%20Day%2...   \n",
       "4                 NaN  http://us.imdb.com/M/title-exact?They%20Made%2...   \n",
       "\n",
       "   unknown  Action  ...  Horror  Musical  Mystery  Romance  Sci-Fi  Thriller  \\\n",
       "0        0       0  ...       0        0        0        0       1         0   \n",
       "1        0       0  ...       0        0        0        0       0         0   \n",
       "2        0       0  ...       0        0        0        0       0         0   \n",
       "3        0       0  ...       0        0        0        0       0         0   \n",
       "4        0       0  ...       0        0        0        0       0         0   \n",
       "\n",
       "   War  Western  ranking_rating_times  ranking_mean_rate  \n",
       "0    0        0                  1450                  0  \n",
       "1    0        0                  1483                  1  \n",
       "2    0        0                  1652                  2  \n",
       "3    0        0                  1661                  3  \n",
       "4    0        0                  1615                  4  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 根据频次大小依次取电影信息\n",
    "df_items_sorted_by_mean_rating_merge = pd.merge(df_items_sorted_by_mean_rating, df_items_sorted_by_rating_times_merge, how='left', left_on='item_id_col', right_on='item_id')\n",
    "df_items_sorted_by_mean_rating_merge['ranking_mean_rate']=range(items_mean_rating.count()) # 加上排名,数字越小，排在越前面\n",
    "\n",
    "df_items_sorted_by_mean_rating_merge.head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "原来这些全 5 分的电影都只有 1-3 个评分！这就把排名排上去了！\n",
    "看来平均分不靠谱，得把评分人次也考虑进去！（总评分？）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'list'>\n",
      "<class 'list'>\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 前二十大流行电影\n",
    "popular_items_count_top_20 = df_items_sorted_by_mean_rating_merge.iloc[0:20]['mean_rating']\n",
    "popular_items_top_20_titles =  df_items_sorted_by_mean_rating_merge.iloc[0:20]['title']\n",
    "\n",
    "objects = list(popular_items_top_20_titles)\n",
    "print(type(objects))\n",
    "y_pos = np.arange(len(objects))\n",
    "performance = list(popular_items_count_top_20)\n",
    "print(type(performance))\n",
    "plt.rcdefaults()    \n",
    "plt.bar(y_pos, performance, align='center', alpha=0.5)\n",
    "plt.xticks(y_pos, objects, rotation='vertical')\n",
    "plt.ylabel('Mean Rating')\n",
    "plt.title('Most popular Movies')\n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_id_col</th>\n",
       "      <th>mean_rating</th>\n",
       "      <th>item_id</th>\n",
       "      <th>rating_times</th>\n",
       "      <th>title</th>\n",
       "      <th>release_date</th>\n",
       "      <th>video_release_date</th>\n",
       "      <th>imdb_url</th>\n",
       "      <th>unknown</th>\n",
       "      <th>Action</th>\n",
       "      <th>...</th>\n",
       "      <th>Horror</th>\n",
       "      <th>Musical</th>\n",
       "      <th>Mystery</th>\n",
       "      <th>Romance</th>\n",
       "      <th>Sci-Fi</th>\n",
       "      <th>Thriller</th>\n",
       "      <th>War</th>\n",
       "      <th>Western</th>\n",
       "      <th>ranking_rating_times</th>\n",
       "      <th>ranking_mean_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>408</td>\n",
       "      <td>4.491071</td>\n",
       "      <td>408</td>\n",
       "      <td>112</td>\n",
       "      <td>Close Shave, A (1995)</td>\n",
       "      <td>28-Apr-1996</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Close%20Shave...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>305</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>318</td>\n",
       "      <td>4.466443</td>\n",
       "      <td>318</td>\n",
       "      <td>298</td>\n",
       "      <td>Schindler's List (1993)</td>\n",
       "      <td>01-Jan-1993</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Schindler's%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>169</td>\n",
       "      <td>4.466102</td>\n",
       "      <td>169</td>\n",
       "      <td>118</td>\n",
       "      <td>Wrong Trousers, The (1993)</td>\n",
       "      <td>01-Jan-1993</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Wrong%20Trous...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>286</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>483</td>\n",
       "      <td>4.456790</td>\n",
       "      <td>483</td>\n",
       "      <td>243</td>\n",
       "      <td>Casablanca (1942)</td>\n",
       "      <td>01-Jan-1942</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Casablanca%20...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>74</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>114</td>\n",
       "      <td>4.447761</td>\n",
       "      <td>114</td>\n",
       "      <td>67</td>\n",
       "      <td>Wallace &amp; Gromit: The Best of Aardman Animatio...</td>\n",
       "      <td>05-Apr-1996</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/Title?Wallace+%26+Gromit%3A...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>483</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>64</td>\n",
       "      <td>4.445230</td>\n",
       "      <td>64</td>\n",
       "      <td>283</td>\n",
       "      <td>Shawshank Redemption, The (1994)</td>\n",
       "      <td>01-Jan-1994</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Shawshank%20R...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>603</td>\n",
       "      <td>4.387560</td>\n",
       "      <td>603</td>\n",
       "      <td>209</td>\n",
       "      <td>Rear Window (1954)</td>\n",
       "      <td>01-Jan-1954</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Rear%20Window...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>106</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>12</td>\n",
       "      <td>4.385768</td>\n",
       "      <td>12</td>\n",
       "      <td>267</td>\n",
       "      <td>Usual Suspects, The (1995)</td>\n",
       "      <td>14-Aug-1995</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Usual%20Suspe...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>55</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>50</td>\n",
       "      <td>4.358491</td>\n",
       "      <td>50</td>\n",
       "      <td>583</td>\n",
       "      <td>Star Wars (1977)</td>\n",
       "      <td>01-Jan-1977</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Star%20Wars%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>178</td>\n",
       "      <td>4.344000</td>\n",
       "      <td>178</td>\n",
       "      <td>125</td>\n",
       "      <td>12 Angry Men (1957)</td>\n",
       "      <td>01-Jan-1957</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?12%20Angry%20...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>263</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    item_id_col  mean_rating  item_id  rating_times  \\\n",
       "15          408     4.491071      408           112   \n",
       "16          318     4.466443      318           298   \n",
       "17          169     4.466102      169           118   \n",
       "18          483     4.456790      483           243   \n",
       "19          114     4.447761      114            67   \n",
       "20           64     4.445230       64           283   \n",
       "21          603     4.387560      603           209   \n",
       "22           12     4.385768       12           267   \n",
       "23           50     4.358491       50           583   \n",
       "24          178     4.344000      178           125   \n",
       "\n",
       "                                                title release_date  \\\n",
       "15                              Close Shave, A (1995)  28-Apr-1996   \n",
       "16                            Schindler's List (1993)  01-Jan-1993   \n",
       "17                         Wrong Trousers, The (1993)  01-Jan-1993   \n",
       "18                                  Casablanca (1942)  01-Jan-1942   \n",
       "19  Wallace & Gromit: The Best of Aardman Animatio...  05-Apr-1996   \n",
       "20                   Shawshank Redemption, The (1994)  01-Jan-1994   \n",
       "21                                 Rear Window (1954)  01-Jan-1954   \n",
       "22                         Usual Suspects, The (1995)  14-Aug-1995   \n",
       "23                                   Star Wars (1977)  01-Jan-1977   \n",
       "24                                12 Angry Men (1957)  01-Jan-1957   \n",
       "\n",
       "    video_release_date                                           imdb_url  \\\n",
       "15                 NaN  http://us.imdb.com/M/title-exact?Close%20Shave...   \n",
       "16                 NaN  http://us.imdb.com/M/title-exact?Schindler's%2...   \n",
       "17                 NaN  http://us.imdb.com/M/title-exact?Wrong%20Trous...   \n",
       "18                 NaN  http://us.imdb.com/M/title-exact?Casablanca%20...   \n",
       "19                 NaN  http://us.imdb.com/Title?Wallace+%26+Gromit%3A...   \n",
       "20                 NaN  http://us.imdb.com/M/title-exact?Shawshank%20R...   \n",
       "21                 NaN  http://us.imdb.com/M/title-exact?Rear%20Window...   \n",
       "22                 NaN  http://us.imdb.com/M/title-exact?Usual%20Suspe...   \n",
       "23                 NaN  http://us.imdb.com/M/title-exact?Star%20Wars%2...   \n",
       "24                 NaN  http://us.imdb.com/M/title-exact?12%20Angry%20...   \n",
       "\n",
       "    unknown  Action  ...  Horror  Musical  Mystery  Romance  Sci-Fi  Thriller  \\\n",
       "15        0       0  ...       0        0        0        0       0         1   \n",
       "16        0       0  ...       0        0        0        0       0         0   \n",
       "17        0       0  ...       0        0        0        0       0         0   \n",
       "18        0       0  ...       0        0        0        1       0         0   \n",
       "19        0       0  ...       0        0        0        0       0         0   \n",
       "20        0       0  ...       0        0        0        0       0         0   \n",
       "21        0       0  ...       0        0        1        0       0         1   \n",
       "22        0       0  ...       0        0        0        0       0         1   \n",
       "23        0       1  ...       0        0        0        1       1         0   \n",
       "24        0       0  ...       0        0        0        0       0         0   \n",
       "\n",
       "    War  Western  ranking_rating_times  ranking_mean_rate  \n",
       "15    0        0                   305                 15  \n",
       "16    1        0                    34                 16  \n",
       "17    0        0                   286                 17  \n",
       "18    1        0                    74                 18  \n",
       "19    0        0                   483                 19  \n",
       "20    0        0                    46                 20  \n",
       "21    0        0                   106                 21  \n",
       "22    0        0                    55                 22  \n",
       "23    1        0                     0                 23  \n",
       "24    0        0                   263                 24  \n",
       "\n",
       "[10 rows x 29 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#去掉评分次数<20次的电影\n",
    "df_items_sorted_by_mean_rating_merge2 = df_items_sorted_by_mean_rating_merge[df_items_sorted_by_mean_rating_merge.rating_times>20]\n",
    "df_items_sorted_by_mean_rating_merge2.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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jowNpDQAA/EMFFFokKSYmRtWrVz+vOx85cqQkqV69ej63jxs3Tp07dz6v2gAA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\nmAKIpwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11b2a5750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 前二十大流行电影\n",
    "popular_items_count_top_20 = df_items_sorted_by_mean_rating_merge2.iloc[0:20]['mean_rating']\n",
    "popular_items_top_20_titles =  df_items_sorted_by_mean_rating_merge2.iloc[0:20]['title']\n",
    "\n",
    "objects = (list(popular_items_top_20_titles))\n",
    "y_pos = np.arange(len(objects))\n",
    "performance = list(popular_items_count_top_20)\n",
    " \n",
    "plt.rcdefaults()    \n",
    "plt.bar(y_pos, performance, align='center', alpha=0.5)\n",
    "plt.xticks(y_pos, objects, rotation='vertical')\n",
    "plt.ylabel('Mean Rating')\n",
    "plt.title('Most popular songs')\n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 评分次数与平均评分的相关性\n",
    "散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 建立一个子图对象\n",
    "fig, ax = plt.subplots(1, 1, figsize=(12, 4))\n",
    "# 散点图\n",
    "ax.scatter(df_items_sorted_by_mean_rating_merge['rating_times'],df_items_sorted_by_mean_rating_merge['mean_rating']);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由上图可见，评分少的不见得就平均分就低，从整体趋势来看，评分次数多的，平均分也高。可见，流行电影确实受人欢迎。从另一个角度看，存在不少广受大众欢迎的电影，但也存在不少看的人不多，但评分很高质量很好的电影，太流行的电影肯定大家都看过了，关键是如何找到那些还比较小众的电影，这些电影可能具备大众欢迎的元素，但因宣传做得不好没被大众发现，也可能是这些电影就是小众，在小圈子里非常受欢迎，但到更大的人群中就不行。如何把这些电影推荐给何时的人，是个性化推荐要考虑的问题。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算电影的年份（从title中来）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_id_col</th>\n",
       "      <th>mean_rating</th>\n",
       "      <th>item_id</th>\n",
       "      <th>rating_times</th>\n",
       "      <th>title</th>\n",
       "      <th>release_date</th>\n",
       "      <th>video_release_date</th>\n",
       "      <th>imdb_url</th>\n",
       "      <th>unknown</th>\n",
       "      <th>Action</th>\n",
       "      <th>...</th>\n",
       "      <th>Musical</th>\n",
       "      <th>Mystery</th>\n",
       "      <th>Romance</th>\n",
       "      <th>Sci-Fi</th>\n",
       "      <th>Thriller</th>\n",
       "      <th>War</th>\n",
       "      <th>Western</th>\n",
       "      <th>ranking_rating_times</th>\n",
       "      <th>ranking_mean_rate</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1293</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1293</td>\n",
       "      <td>3</td>\n",
       "      <td>Star Kid (1997)</td>\n",
       "      <td>16-Jan-1998</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?imdb-title-12...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1450</td>\n",
       "      <td>0</td>\n",
       "      <td>1997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1467</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1467</td>\n",
       "      <td>2</td>\n",
       "      <td>Saint of Fort Washington, The (1993)</td>\n",
       "      <td>01-Jan-1993</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Saint%20of%20...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1483</td>\n",
       "      <td>1</td>\n",
       "      <td>1993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1653</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1653</td>\n",
       "      <td>1</td>\n",
       "      <td>Entertaining Angels: The Dorothy Day Story (1996)</td>\n",
       "      <td>27-Sep-1996</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Entertaining%...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1652</td>\n",
       "      <td>2</td>\n",
       "      <td>1996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>814</td>\n",
       "      <td>5.0</td>\n",
       "      <td>814</td>\n",
       "      <td>1</td>\n",
       "      <td>Great Day in Harlem, A (1994)</td>\n",
       "      <td>01-Jan-1994</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Great%20Day%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1661</td>\n",
       "      <td>3</td>\n",
       "      <td>1994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1122</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1122</td>\n",
       "      <td>1</td>\n",
       "      <td>They Made Me a Criminal (1939)</td>\n",
       "      <td>01-Jan-1939</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?They%20Made%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1615</td>\n",
       "      <td>4</td>\n",
       "      <td>1939</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   item_id_col  mean_rating  item_id  rating_times  \\\n",
       "0         1293          5.0     1293             3   \n",
       "1         1467          5.0     1467             2   \n",
       "2         1653          5.0     1653             1   \n",
       "3          814          5.0      814             1   \n",
       "4         1122          5.0     1122             1   \n",
       "\n",
       "                                               title release_date  \\\n",
       "0                                    Star Kid (1997)  16-Jan-1998   \n",
       "1               Saint of Fort Washington, The (1993)  01-Jan-1993   \n",
       "2  Entertaining Angels: The Dorothy Day Story (1996)  27-Sep-1996   \n",
       "3                      Great Day in Harlem, A (1994)  01-Jan-1994   \n",
       "4                     They Made Me a Criminal (1939)  01-Jan-1939   \n",
       "\n",
       "   video_release_date                                           imdb_url  \\\n",
       "0                 NaN  http://us.imdb.com/M/title-exact?imdb-title-12...   \n",
       "1                 NaN  http://us.imdb.com/M/title-exact?Saint%20of%20...   \n",
       "2                 NaN  http://us.imdb.com/M/title-exact?Entertaining%...   \n",
       "3                 NaN  http://us.imdb.com/M/title-exact?Great%20Day%2...   \n",
       "4                 NaN  http://us.imdb.com/M/title-exact?They%20Made%2...   \n",
       "\n",
       "   unknown  Action  ...  Musical  Mystery  Romance  Sci-Fi  Thriller  War  \\\n",
       "0        0       0  ...        0        0        0       1         0    0   \n",
       "1        0       0  ...        0        0        0       0         0    0   \n",
       "2        0       0  ...        0        0        0       0         0    0   \n",
       "3        0       0  ...        0        0        0       0         0    0   \n",
       "4        0       0  ...        0        0        0       0         0    0   \n",
       "\n",
       "   Western  ranking_rating_times  ranking_mean_rate  year  \n",
       "0        0                  1450                  0  1997  \n",
       "1        0                  1483                  1  1993  \n",
       "2        0                  1652                  2  1996  \n",
       "3        0                  1661                  3  1994  \n",
       "4        0                  1615                  4  1939  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# print(df_items_sorted_by_mean_rating_merge.title.str)\n",
    "# print(df_items_sorted_by_mean_rating_merge.title.str.extract('(\\((\\d{4})\\))', expand=True))\n",
    "\n",
    "# 使用正则表达式取出上映年份\n",
    "df_items_sorted_by_mean_rating_merge['year'] = df_items_sorted_by_mean_rating_merge.title.str.extract('(\\((\\d{4})\\))', expand=True).iloc[:,1] \n",
    "df_items_sorted_by_mean_rating_merge.head()\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#去掉年份后的Title\n",
    "#import re\n",
    "#pattern = re.compile(r'^(.*)\\((\\d+)\\)$')\n",
    "#title_map = {val:pattern.match(val).group(1) for ii,val in enumerate(set(df_items_sorted_by_mean_rating_merge['title']))}\n",
    "#df_items_sorted_by_mean_rating_merge['title'] = df_items_sorted_by_mean_rating_merge['title'].map(title_map)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "#统计每年上映的电影数目，默认是降序排列\n",
    "items_sorted_by_year = df_items_sorted_by_mean_rating_merge['year'].value_counts() \n",
    "# print(items_sorted_by_year)\n",
    "# print(type(df_items_sorted_by_mean_rating_merge['year']))\n",
    "# print(type(items_sorted_by_year))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x114262550>"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, figsize=(15, 12))\n",
    "items_sorted_by_year.plot(kind='bar', title='freq')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
